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Record W2059932935 · doi:10.1117/1.1383779

Imaging of whole tumor cut sections using a novel scanning beam confocal fluorescence MACROscope®

2001· article· en· W2059932935 on OpenAlexafffund
Vojislav Vukovic, Hans Kristian Haugland, Trudey Nicklee, David W. Hedley, Brian C. Wilson

Bibliographic record

VenueJournal of Biomedical Optics · 2001
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoOntario Institute for Cancer Research
FundersNational Cancer InstituteUniversity of Waterloo
KeywordsFluorescenceConfocalMaterials scienceOpticsFluorescence-lifetime imaging microscopyBeam (structure)Confocal microscopyBiomedical engineeringMedicinePhysics

Abstract

fetched live from OpenAlex

Hypoxia caused by inadequate structure and function of the tumor vasculature has been found to negatively determine the prognosis of cancer patients. Hence, understanding the biological basis of tumor hypoxia is of significant clinical interest. To study solid tumor microenvironments in sufficient detail, large areas (several mm in diameter) need to be imaged at microm resolutions. We have used a novel confocal scanning laser MACROscope (CSLM) capable of acquiring images over fields of view up to 2cm x 2cm. To demonstrate its performance, frozen sections from a cervical carcinoma xenograft were triple labeled for tissue hypoxia, blood vessels and hypoxia-inducible transcription factor 1 alpha (HIF-1alpha), imaged using the CSLM and compared to images obtained using a standard epifluorescence microscope imaging system. The results indicate that the CSLM is a useful instrument for imaging tissue-based fluorescence at resolutions comparable to standard low-power microscope objectives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.284
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2001
Admission routes2
Has abstractyes

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